---
title: 'Custom Agents Overview'
description: 'Building your own agents for the Open Agent Platform'
---

# Building Your Own Agents

We built Open Agent Platform with custom agents in mind. Although we offer a few pre-built agents, we encourage you to build your own agents, and use OAP as a platform to prototype, test and use them! This guide will help you build agents that are compatible with all of Open Agent Platform's features.

## Platform Requirements

OAP is built on top of LangGraph Platform, which means all agents which you build to be used in OAP must be LangGraph agents deployed on LangGraph Platform.

## Agent Types

When building custom agents, you can create three main types:

1. **Standard Agents**: These are single-purpose agents that handle specific tasks.
2. **Tools Agents**: Agents that can access external tools via the MCP protocol.
3. **Supervisor Agents**: Agents that can orchestrate and coordinate multiple other agents.

## Development Flow

The typical development flow for creating custom agents involves:

1. Developing and testing your agent locally using LangGraph
2. Deploying your agent to LangGraph Platform
3. Configuring your Open Agent Platform to connect to your deployed agent
4. Testing and refining your agent through the OAP interface

## Getting Started

To get started with building your own agents, we recommend:

1. Familiarizing yourself with the [LangGraph framework](https://github.com/langchain-ai/langgraph)
2. Studying the example agents we provide:
   - [Tools Agent](https://github.com/langchain-ai/oap-langgraph-tools-agent)
   - [Supervisor Agent](https://github.com/langchain-ai/oap-agent-supervisor)
   - [Deep Research Agent](https://github.com/langchain-ai/oap-deep-researcher)
3. Understanding how to make your agent configurable, as detailed in the [Configuration](/labs/oap/custom-agents/configuration) section

Building custom agents allows you to create specialized AI assistants that can be easily managed and used through the Open Agent Platform interface.
